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<FONT color="green">001</FONT>    /*<a name="line.1"></a>
<FONT color="green">002</FONT>     * Licensed to the Apache Software Foundation (ASF) under one or more<a name="line.2"></a>
<FONT color="green">003</FONT>     * contributor license agreements.  See the NOTICE file distributed with<a name="line.3"></a>
<FONT color="green">004</FONT>     * this work for additional information regarding copyright ownership.<a name="line.4"></a>
<FONT color="green">005</FONT>     * The ASF licenses this file to You under the Apache License, Version 2.0<a name="line.5"></a>
<FONT color="green">006</FONT>     * (the "License"); you may not use this file except in compliance with<a name="line.6"></a>
<FONT color="green">007</FONT>     * the License.  You may obtain a copy of the License at<a name="line.7"></a>
<FONT color="green">008</FONT>     *<a name="line.8"></a>
<FONT color="green">009</FONT>     *      http://www.apache.org/licenses/LICENSE-2.0<a name="line.9"></a>
<FONT color="green">010</FONT>     *<a name="line.10"></a>
<FONT color="green">011</FONT>     * Unless required by applicable law or agreed to in writing, software<a name="line.11"></a>
<FONT color="green">012</FONT>     * distributed under the License is distributed on an "AS IS" BASIS,<a name="line.12"></a>
<FONT color="green">013</FONT>     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.<a name="line.13"></a>
<FONT color="green">014</FONT>     * See the License for the specific language governing permissions and<a name="line.14"></a>
<FONT color="green">015</FONT>     * limitations under the License.<a name="line.15"></a>
<FONT color="green">016</FONT>     */<a name="line.16"></a>
<FONT color="green">017</FONT>    <a name="line.17"></a>
<FONT color="green">018</FONT>    package org.apache.commons.math.stat.correlation;<a name="line.18"></a>
<FONT color="green">019</FONT>    <a name="line.19"></a>
<FONT color="green">020</FONT>    import org.apache.commons.math.MathRuntimeException;<a name="line.20"></a>
<FONT color="green">021</FONT>    import org.apache.commons.math.exception.util.LocalizedFormats;<a name="line.21"></a>
<FONT color="green">022</FONT>    import org.apache.commons.math.linear.BlockRealMatrix;<a name="line.22"></a>
<FONT color="green">023</FONT>    import org.apache.commons.math.linear.RealMatrix;<a name="line.23"></a>
<FONT color="green">024</FONT>    import org.apache.commons.math.stat.ranking.NaturalRanking;<a name="line.24"></a>
<FONT color="green">025</FONT>    import org.apache.commons.math.stat.ranking.RankingAlgorithm;<a name="line.25"></a>
<FONT color="green">026</FONT>    <a name="line.26"></a>
<FONT color="green">027</FONT>    /**<a name="line.27"></a>
<FONT color="green">028</FONT>     * &lt;p&gt;Spearman's rank correlation. This implementation performs a rank<a name="line.28"></a>
<FONT color="green">029</FONT>     * transformation on the input data and then computes {@link PearsonsCorrelation}<a name="line.29"></a>
<FONT color="green">030</FONT>     * on the ranked data.&lt;/p&gt;<a name="line.30"></a>
<FONT color="green">031</FONT>     *<a name="line.31"></a>
<FONT color="green">032</FONT>     * &lt;p&gt;By default, ranks are computed using {@link NaturalRanking} with default<a name="line.32"></a>
<FONT color="green">033</FONT>     * strategies for handling NaNs and ties in the data (NaNs maximal, ties averaged).<a name="line.33"></a>
<FONT color="green">034</FONT>     * The ranking algorithm can be set using a constructor argument.&lt;/p&gt;<a name="line.34"></a>
<FONT color="green">035</FONT>     *<a name="line.35"></a>
<FONT color="green">036</FONT>     * @since 2.0<a name="line.36"></a>
<FONT color="green">037</FONT>     * @version $Revision: 983921 $ $Date: 2010-08-10 12:46:06 +0200 (mar. 10 ao??t 2010) $<a name="line.37"></a>
<FONT color="green">038</FONT>     */<a name="line.38"></a>
<FONT color="green">039</FONT>    <a name="line.39"></a>
<FONT color="green">040</FONT>    public class SpearmansCorrelation {<a name="line.40"></a>
<FONT color="green">041</FONT>    <a name="line.41"></a>
<FONT color="green">042</FONT>        /** Input data */<a name="line.42"></a>
<FONT color="green">043</FONT>        private final RealMatrix data;<a name="line.43"></a>
<FONT color="green">044</FONT>    <a name="line.44"></a>
<FONT color="green">045</FONT>        /** Ranking algorithm  */<a name="line.45"></a>
<FONT color="green">046</FONT>        private final RankingAlgorithm rankingAlgorithm;<a name="line.46"></a>
<FONT color="green">047</FONT>    <a name="line.47"></a>
<FONT color="green">048</FONT>        /** Rank correlation */<a name="line.48"></a>
<FONT color="green">049</FONT>        private final PearsonsCorrelation rankCorrelation;<a name="line.49"></a>
<FONT color="green">050</FONT>    <a name="line.50"></a>
<FONT color="green">051</FONT>        /**<a name="line.51"></a>
<FONT color="green">052</FONT>         * Create a SpearmansCorrelation with the given input data matrix<a name="line.52"></a>
<FONT color="green">053</FONT>         * and ranking algorithm.<a name="line.53"></a>
<FONT color="green">054</FONT>         *<a name="line.54"></a>
<FONT color="green">055</FONT>         * @param dataMatrix matrix of data with columns representing<a name="line.55"></a>
<FONT color="green">056</FONT>         * variables to correlate<a name="line.56"></a>
<FONT color="green">057</FONT>         * @param rankingAlgorithm ranking algorithm<a name="line.57"></a>
<FONT color="green">058</FONT>         */<a name="line.58"></a>
<FONT color="green">059</FONT>        public SpearmansCorrelation(final RealMatrix dataMatrix, final RankingAlgorithm rankingAlgorithm) {<a name="line.59"></a>
<FONT color="green">060</FONT>            this.data = dataMatrix.copy();<a name="line.60"></a>
<FONT color="green">061</FONT>            this.rankingAlgorithm = rankingAlgorithm;<a name="line.61"></a>
<FONT color="green">062</FONT>            rankTransform(data);<a name="line.62"></a>
<FONT color="green">063</FONT>            rankCorrelation = new PearsonsCorrelation(data);<a name="line.63"></a>
<FONT color="green">064</FONT>        }<a name="line.64"></a>
<FONT color="green">065</FONT>    <a name="line.65"></a>
<FONT color="green">066</FONT>        /**<a name="line.66"></a>
<FONT color="green">067</FONT>         * Create a SpearmansCorrelation from the given data matrix.<a name="line.67"></a>
<FONT color="green">068</FONT>         *<a name="line.68"></a>
<FONT color="green">069</FONT>         * @param dataMatrix matrix of data with columns representing<a name="line.69"></a>
<FONT color="green">070</FONT>         * variables to correlate<a name="line.70"></a>
<FONT color="green">071</FONT>         */<a name="line.71"></a>
<FONT color="green">072</FONT>        public SpearmansCorrelation(final RealMatrix dataMatrix) {<a name="line.72"></a>
<FONT color="green">073</FONT>            this(dataMatrix, new NaturalRanking());<a name="line.73"></a>
<FONT color="green">074</FONT>        }<a name="line.74"></a>
<FONT color="green">075</FONT>    <a name="line.75"></a>
<FONT color="green">076</FONT>        /**<a name="line.76"></a>
<FONT color="green">077</FONT>         * Create a SpearmansCorrelation without data.<a name="line.77"></a>
<FONT color="green">078</FONT>         */<a name="line.78"></a>
<FONT color="green">079</FONT>        public SpearmansCorrelation() {<a name="line.79"></a>
<FONT color="green">080</FONT>            data = null;<a name="line.80"></a>
<FONT color="green">081</FONT>            this.rankingAlgorithm = new NaturalRanking();<a name="line.81"></a>
<FONT color="green">082</FONT>            rankCorrelation = null;<a name="line.82"></a>
<FONT color="green">083</FONT>        }<a name="line.83"></a>
<FONT color="green">084</FONT>    <a name="line.84"></a>
<FONT color="green">085</FONT>        /**<a name="line.85"></a>
<FONT color="green">086</FONT>         * Calculate the Spearman Rank Correlation Matrix.<a name="line.86"></a>
<FONT color="green">087</FONT>         *<a name="line.87"></a>
<FONT color="green">088</FONT>         * @return Spearman Rank Correlation Matrix<a name="line.88"></a>
<FONT color="green">089</FONT>         */<a name="line.89"></a>
<FONT color="green">090</FONT>        public RealMatrix getCorrelationMatrix() {<a name="line.90"></a>
<FONT color="green">091</FONT>            return rankCorrelation.getCorrelationMatrix();<a name="line.91"></a>
<FONT color="green">092</FONT>        }<a name="line.92"></a>
<FONT color="green">093</FONT>    <a name="line.93"></a>
<FONT color="green">094</FONT>        /**<a name="line.94"></a>
<FONT color="green">095</FONT>         * Returns a {@link PearsonsCorrelation} instance constructed from the<a name="line.95"></a>
<FONT color="green">096</FONT>         * ranked input data. That is,<a name="line.96"></a>
<FONT color="green">097</FONT>         * &lt;code&gt;new SpearmansCorrelation(matrix).getRankCorrelation()&lt;/code&gt;<a name="line.97"></a>
<FONT color="green">098</FONT>         * is equivalent to<a name="line.98"></a>
<FONT color="green">099</FONT>         * &lt;code&gt;new PearsonsCorrelation(rankTransform(matrix))&lt;/code&gt; where<a name="line.99"></a>
<FONT color="green">100</FONT>         * &lt;code&gt;rankTransform(matrix)&lt;/code&gt; is the result of applying the<a name="line.100"></a>
<FONT color="green">101</FONT>         * configured &lt;code&gt;RankingAlgorithm&lt;/code&gt; to each of the columns of<a name="line.101"></a>
<FONT color="green">102</FONT>         * &lt;code&gt;matrix.&lt;/code&gt;<a name="line.102"></a>
<FONT color="green">103</FONT>         *<a name="line.103"></a>
<FONT color="green">104</FONT>         * @return PearsonsCorrelation among ranked column data<a name="line.104"></a>
<FONT color="green">105</FONT>         */<a name="line.105"></a>
<FONT color="green">106</FONT>        public PearsonsCorrelation getRankCorrelation() {<a name="line.106"></a>
<FONT color="green">107</FONT>            return rankCorrelation;<a name="line.107"></a>
<FONT color="green">108</FONT>        }<a name="line.108"></a>
<FONT color="green">109</FONT>    <a name="line.109"></a>
<FONT color="green">110</FONT>        /**<a name="line.110"></a>
<FONT color="green">111</FONT>         * Computes the Spearman's rank correlation matrix for the columns of the<a name="line.111"></a>
<FONT color="green">112</FONT>         * input matrix.<a name="line.112"></a>
<FONT color="green">113</FONT>         *<a name="line.113"></a>
<FONT color="green">114</FONT>         * @param matrix matrix with columns representing variables to correlate<a name="line.114"></a>
<FONT color="green">115</FONT>         * @return correlation matrix<a name="line.115"></a>
<FONT color="green">116</FONT>         */<a name="line.116"></a>
<FONT color="green">117</FONT>        public RealMatrix computeCorrelationMatrix(RealMatrix matrix) {<a name="line.117"></a>
<FONT color="green">118</FONT>            RealMatrix matrixCopy = matrix.copy();<a name="line.118"></a>
<FONT color="green">119</FONT>            rankTransform(matrixCopy);<a name="line.119"></a>
<FONT color="green">120</FONT>            return new PearsonsCorrelation().computeCorrelationMatrix(matrixCopy);<a name="line.120"></a>
<FONT color="green">121</FONT>        }<a name="line.121"></a>
<FONT color="green">122</FONT>    <a name="line.122"></a>
<FONT color="green">123</FONT>        /**<a name="line.123"></a>
<FONT color="green">124</FONT>         * Computes the Spearman's rank correlation matrix for the columns of the<a name="line.124"></a>
<FONT color="green">125</FONT>         * input rectangular array.  The columns of the array represent values<a name="line.125"></a>
<FONT color="green">126</FONT>         * of variables to be correlated.<a name="line.126"></a>
<FONT color="green">127</FONT>         *<a name="line.127"></a>
<FONT color="green">128</FONT>         * @param matrix matrix with columns representing variables to correlate<a name="line.128"></a>
<FONT color="green">129</FONT>         * @return correlation matrix<a name="line.129"></a>
<FONT color="green">130</FONT>         */<a name="line.130"></a>
<FONT color="green">131</FONT>        public RealMatrix computeCorrelationMatrix(double[][] matrix) {<a name="line.131"></a>
<FONT color="green">132</FONT>           return computeCorrelationMatrix(new BlockRealMatrix(matrix));<a name="line.132"></a>
<FONT color="green">133</FONT>        }<a name="line.133"></a>
<FONT color="green">134</FONT>    <a name="line.134"></a>
<FONT color="green">135</FONT>        /**<a name="line.135"></a>
<FONT color="green">136</FONT>         * Computes the Spearman's rank correlation coefficient between the two arrays.<a name="line.136"></a>
<FONT color="green">137</FONT>         *<a name="line.137"></a>
<FONT color="green">138</FONT>         * &lt;/p&gt;Throws IllegalArgumentException if the arrays do not have the same length<a name="line.138"></a>
<FONT color="green">139</FONT>         * or their common length is less than 2&lt;/p&gt;<a name="line.139"></a>
<FONT color="green">140</FONT>         *<a name="line.140"></a>
<FONT color="green">141</FONT>         * @param xArray first data array<a name="line.141"></a>
<FONT color="green">142</FONT>         * @param yArray second data array<a name="line.142"></a>
<FONT color="green">143</FONT>         * @return Returns Spearman's rank correlation coefficient for the two arrays<a name="line.143"></a>
<FONT color="green">144</FONT>         * @throws  IllegalArgumentException if the arrays lengths do not match or<a name="line.144"></a>
<FONT color="green">145</FONT>         * there is insufficient data<a name="line.145"></a>
<FONT color="green">146</FONT>         */<a name="line.146"></a>
<FONT color="green">147</FONT>        public double correlation(final double[] xArray, final double[] yArray)<a name="line.147"></a>
<FONT color="green">148</FONT>        throws IllegalArgumentException {<a name="line.148"></a>
<FONT color="green">149</FONT>            if (xArray.length != yArray.length) {<a name="line.149"></a>
<FONT color="green">150</FONT>                throw MathRuntimeException.createIllegalArgumentException(<a name="line.150"></a>
<FONT color="green">151</FONT>                      LocalizedFormats.DIMENSIONS_MISMATCH_SIMPLE, xArray.length, yArray.length);<a name="line.151"></a>
<FONT color="green">152</FONT>            } else if (xArray.length &lt; 2) {<a name="line.152"></a>
<FONT color="green">153</FONT>                throw MathRuntimeException.createIllegalArgumentException(<a name="line.153"></a>
<FONT color="green">154</FONT>                      LocalizedFormats.INSUFFICIENT_DIMENSION, xArray.length, 2);<a name="line.154"></a>
<FONT color="green">155</FONT>            } else {<a name="line.155"></a>
<FONT color="green">156</FONT>                return new PearsonsCorrelation().correlation(rankingAlgorithm.rank(xArray),<a name="line.156"></a>
<FONT color="green">157</FONT>                        rankingAlgorithm.rank(yArray));<a name="line.157"></a>
<FONT color="green">158</FONT>            }<a name="line.158"></a>
<FONT color="green">159</FONT>        }<a name="line.159"></a>
<FONT color="green">160</FONT>    <a name="line.160"></a>
<FONT color="green">161</FONT>        /**<a name="line.161"></a>
<FONT color="green">162</FONT>         * Applies rank transform to each of the columns of &lt;code&gt;matrix&lt;/code&gt;<a name="line.162"></a>
<FONT color="green">163</FONT>         * using the current &lt;code&gt;rankingAlgorithm&lt;/code&gt;<a name="line.163"></a>
<FONT color="green">164</FONT>         *<a name="line.164"></a>
<FONT color="green">165</FONT>         * @param matrix matrix to transform<a name="line.165"></a>
<FONT color="green">166</FONT>         */<a name="line.166"></a>
<FONT color="green">167</FONT>        private void rankTransform(RealMatrix matrix) {<a name="line.167"></a>
<FONT color="green">168</FONT>            for (int i = 0; i &lt; matrix.getColumnDimension(); i++) {<a name="line.168"></a>
<FONT color="green">169</FONT>                matrix.setColumn(i, rankingAlgorithm.rank(matrix.getColumn(i)));<a name="line.169"></a>
<FONT color="green">170</FONT>            }<a name="line.170"></a>
<FONT color="green">171</FONT>        }<a name="line.171"></a>
<FONT color="green">172</FONT>    }<a name="line.172"></a>




























































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